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join us as a PhD candidate. You will work in a highly interdisciplinary group, at the intersection of physics, machine learning and theoretical neuroscience. Our group is focused on investigating
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single-cell proteomics approaches on patient samples to gain additional resolution on cell-state diversity within tumours. In parallel, you will collaborate closely with a postdoctoral researcher to
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condensed matter physics on one of the topics listed below. You will actively cooperate with other PhD candidates, postdoctoral researchers and staff of HFML‐FELIX working on related topics, and you will be
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on cell-state diversity within tumours. In parallel, you will collaborate closely with a postdoctoral researcher to develop and apply novel proximity-labelling strategies to chart dynamic protein–protein
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recent advances in machine learning and browser automation, the project aims to provide tools, techniques and datasets to effectively address these threats. As a PhD candidate, you will play a key role in
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or computational neuroscience/machine learning. You possess solid programming and software engineering skills. You have excellent written and spoken English skills. You are a proactive team player, who enjoys
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. Would you like to learn more about what it’s like to pursue a PhD at Radboud University? Visit the page about working as a PhD candidate . A PhD track at Radboud University gives you room to follow your
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-ACCENT project aims to fill this gap by combining insights from cognitive psychology, neuroscience, AI engineering, human-computer interaction and social science, with lifespan perspectives. Using advanced
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. Would you like to learn more about what it’s like to pursue a PhD at Radboud University? Visit the page about working as a PhD candidate . I quickly found my rhythm at Radboud University because
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, secondments and network training activities. Your teaching load may be up to 10% of your working time. You will also have opportunities to develop your teaching skills. Would you like to learn more about what